-LAN- 25785d8c3f refactor(knowledge-retrieval): improve error handling with custom exceptions (#10385) 5 meses atrás
..
.idea 7ae728a9a3 fix nltk averaged_perceptron_tagger download and fix score limit is none (#7582) 8 meses atrás
.vscode e61752bd3a feat/enhance the multi-modal support (#8818) 6 meses atrás
configs 444c1f170a fix typo: mMaximum -> Maximum (#10389) 5 meses atrás
constants 3e9d271b52 nltk security issue and upgrade unstructured (#9558) 6 meses atrás
contexts e61752bd3a feat/enhance the multi-modal support (#8818) 6 meses atrás
controllers 1ccca7cc68 fixed: web api remote urls error (#10383) 5 meses atrás
core 25785d8c3f refactor(knowledge-retrieval): improve error handling with custom exceptions (#10385) 5 meses atrás
docker 8dfdb37de3 fix: use LOG_LEVEL for celery startup (#7628) 8 meses atrás
events e61752bd3a feat/enhance the multi-modal support (#8818) 6 meses atrás
extensions 0a3d51e9cf Revert "chore: improve validation and handler of logging timezone with TimezoneName" (#10077) 5 meses atrás
factories 7962101e5e fix: iteration none output error (#10295) 5 meses atrás
fields 6452342222 feat(workflow): add configurable workflow file upload limit (#10176) 5 meses atrás
libs d3e9930235 refactor(question_classifier): improve error handling with custom exceptions (#10365) 5 meses atrás
migrations bf048b8d7c refactor(migration/model): update column types for workflow schema (#10160) 5 meses atrás
models 249b897872 feat(model): add validation for custom disclaimer length (#10287) 5 meses atrás
schedule 07ad362854 fix: Cannot find declaration to go to CLEAN_DAY_SETTING (#10157) 5 meses atrás
services d45d90e8ae chore: lazy import sagemaker (#10342) 5 meses atrás
tasks 4fd2743efa Feat/new login (#8120) 6 meses atrás
templates 4fd2743efa Feat/new login (#8120) 6 meses atrás
tests 7962101e5e fix: iteration none output error (#10295) 5 meses atrás
.dockerignore 27f0ae8416 build: support Poetry for depencencies tool in api's Dockerfile (#5105) 10 meses atrás
.env.example 12a9e2972a Adjusted docker manifests and environment variables for OceanBase vector database (#10395) 5 meses atrás
Dockerfile 87c1de66f2 chore(Dockerfile): upgrade zlib arm64 (#10244) 5 meses atrás
README.md eafe5a9d8f chore(ci): bring back poetry cache to speed up CI jobs (#10347) 5 meses atrás
app.py 4d9160ca9f refactor: use dify_config to replace legacy usage of flask app's config (#9089) 6 meses atrás
app_factory.py 4d9160ca9f refactor: use dify_config to replace legacy usage of flask app's config (#9089) 6 meses atrás
commands.py 878d13ef42 Added OceanBase as an option for the vector store in Dify (#10010) 5 meses atrás
poetry.lock d45d90e8ae chore: lazy import sagemaker (#10342) 5 meses atrás
poetry.toml f62f71a81a build: initial support for poetry build tool (#4513) 10 meses atrás
pyproject.toml d45d90e8ae chore: lazy import sagemaker (#10342) 5 meses atrás
pytest.ini 0ebd985672 feat: add models for gitee.ai (#9490) 5 meses atrás

README.md

Dify Backend API

Usage

[!IMPORTANT] In the v0.6.12 release, we deprecated pip as the package management tool for Dify API Backend service and replaced it with poetry.

  1. Start the docker-compose stack

The backend require some middleware, including PostgreSQL, Redis, and Weaviate, which can be started together using docker-compose.

   cd ../docker
   cp middleware.env.example middleware.env
   # change the profile to other vector database if you are not using weaviate
   docker compose -f docker-compose.middleware.yaml --profile weaviate -p dify up -d
   cd ../api
  1. Copy .env.example to .env
  2. Generate a SECRET_KEY in the .env file.
   sed -i "/^SECRET_KEY=/c\SECRET_KEY=$(openssl rand -base64 42)" .env
   secret_key=$(openssl rand -base64 42)
   sed -i '' "/^SECRET_KEY=/c\\
   SECRET_KEY=${secret_key}" .env
  1. Create environment.

Dify API service uses Poetry to manage dependencies. You can execute poetry shell to activate the environment.

  1. Install dependencies
   poetry env use 3.10
   poetry install

In case of contributors missing to update dependencies for pyproject.toml, you can perform the following shell instead.

   poetry shell                                               # activate current environment
   poetry add $(cat requirements.txt)           # install dependencies of production and update pyproject.toml
   poetry add $(cat requirements-dev.txt) --group dev    # install dependencies of development and update pyproject.toml
  1. Run migrate

Before the first launch, migrate the database to the latest version.

   poetry run python -m flask db upgrade
  1. Start backend
   poetry run python -m flask run --host 0.0.0.0 --port=5001 --debug
  1. Start Dify web service.
  2. Setup your application by visiting http://localhost:3000...
  3. If you need to handle and debug the async tasks (e.g. dataset importing and documents indexing), please start the worker service.
   poetry run python -m celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion

Testing

  1. Install dependencies for both the backend and the test environment
   poetry install -C api --with dev
  1. Run the tests locally with mocked system environment variables in tool.pytest_env section in pyproject.toml
   poetry run -C api bash dev/pytest/pytest_all_tests.sh